martes, marzo 19, 2013

Spring Data Neo4j

Spring Data Neo4j is the project within Spring Data project which provides an extension to the Spring programming model for writing applications that uses Neo4j as graph database.

To write tests using NoSQLUnit for Spring Data Neo4j applications, you do need nothing special apart from considering that Spring Data Neo4j uses a special property called type in graph nodes and relationships which stores the fully qualified classname of that entity.

Apart from type property at node/relationship level, we also need to create one index for nodes and one index for relationships. In case of nodes, types index name is required, meanwhile rel_types is required for relationships. In both cases we must set key value to className and value to full qualified classname.

Type mappingIndexingNodeTypeRepresentationStrategy and IndexingRelationshipTypeRepresentationStrategy are used as default type mapping implementation, but you can also use SubReferenceNodeTypeRepresentationStrategy which stores entity types in a tree in the graph representing the type and interface hierarchy, or you can customize even more by implementing NodeTypeRepresentationStrategy interface.

Hands on Work

Application

Starfleet has asked us to develop an application for storing all starfleet members, with their relationship with other starfleet members, and the ship where they serve.

The best way to implement this requirement is using Neo4j database as backend system. Moreover Spring Data Neo4j is used at persistence layer.

This application is modelized into two Java classes, one for members and another one for starships. Note that for this example there are no properties in relationships, so only nodes are modelized.

See that apart from operations provided by GrapRepository interface like save, findAll, findById, … we are defining one query method too called findByName. Spring Data Neo4j repositories (and most of Spring Data projects) provide a mechanism to define queries using the known Ruby on Rails approach for defining finder queries.

Testing

Unit Testing

As it has been told previously, for writing datasets for Spring Data Neo4j, we don’t have to do anything special beyond creating node and relationship properties correctly and defining the required indexes. Let’s see the dataset used to test the findByName method by seeding Neo4j database.

There are some important points in the previous class to take under consideration:

Recall that we need to use SpringApplicationContext object to retrieve embedded Neo4j instance defined into Spring application context.

Since lifecycle of database is managed by Spring Data container, there is no need to define any NoSQLUnit lifecycle manager.

Integration Test

Unit tests are usually run against embedded in-memory instances, but in production environment you may require access to external Neo4j servers by using Rest connection, or in case of Spring Data Neo4j instantiating SpringRestGraphDatabase class. You need to write tests to validate that your application still works when you integrate your code with a remote server, and this tests are typically known as integration tests.

To write integration tests for our application is as easy as defining an application context with SpringRestGraphDatabase and allow NoSQLUnit to control the lifecycle of Neo4j database.

Note how instead of registering an embedded instance, we are configuring SpringRestGraphDatabase class to connect to localhost server. And let’s implement an integration test which verifies that all starships can be retrieved from Neo4j server.

Because defaultSpringGraphDatabaseServiceNeo4j method returns a GraphDatabaseService instance defined into application context, in our case it will return the defined SpringRestGraphDatabase instance.

Conclusions

There is not much difference between writing tests for none Spring Data Neo4j applications than the ones they use it. Only keep in mind to define correctly the type property and create required indexes.

Also see that from the point of view of NoSQLUnit there is no difference between writing unit or integration tests, apart of lifecycle management of the database engine.